Basic ecology rests firmly on a number of basic assumptions. Some of these assumptions, specifically how predators interaction with their prey, were developed by a key figure in the history of resilience – Buzz Holling. The Holling type I, II and III functional responses are standard material in many textbooks in ecology (here’s wikipedia on functional response). The different functional responses reflect the prey consumption ratio as a function of food density. I learned about these different types of functional response more than a decade before coming across anything related to resilience theory, which is perhaps not surprising as the first papers published by Holling on the topic came out in the late 1950s (Holling 1959).

The different functional responses reflect different ways in which predator consumption of prey varies with changes in food density. The functional response is also related to the numerical response – the reproduction rate in relation to food abundance. If this is too technical, bear with me.

Different types of functional response.

As shown above, a type I functional response is linear – meaning that more prey means that more prey are consumed – straightforward and simple. A type II response is non-linear – the number of prey consumed/reproduction increases initially but reaches a plateau at a certain prey density, as the predator ability to consume prey is gradually saturated. A type III response is more complex and S shaped, with a slow increase in prey consumed/reproduction, due to difficulty in discovering prey, followed by an increase and subsequent leveling off, as predators are saturated (for more background see here).

What has all this got to do with seabirds?

Seabirds are some of the most conspicuous components of the marine environment and are also well studied throughout the world. Many places where seabirds are studied also have monitoring programs for their prey. Seabirds prey on small pelagic, fat schooling fish – some of which are very important in the rapidly growing aquaculture and meat production sectors.

Recently, I was part of a large group of scientists who analyzed long-term data collected of seabird breeding success, for a range of seabird species breeding throughout the world, including puffins, murres, gulls and penguins. Several of these data sets had previously indicated a type I, or possibly a type II response in some instances, but the evidence were inconclusive. However – when putting all the data together, an interesting pattern emerged – the data indicated a clear type II response!What was even more interesting was that this response was consistent across ecosystems and species. All ecosystems and species investigated had a very similar level of the threshold – regardless of latitude or foraging strategy. Although we assumed that there would be some nonlinear response in all ecosystems and species, we did not think the threshold would be so similar in where it was located (i.e., at one third of the maximum observed fish biomass).

The key figure from our paper is below.

Fig. 2 (A) Relationship between normalized annual breeding success of seabirds and normalized prey abundance. Each data point from all the time series was plotted with the predictions of a generalized additive model (GAM) (solid line). The gray area represents the 95% confidence interval of the fitted GAM. The threshold in the nonlinear relationship (black solid vertical line) and its 95% confidence interval (black dashed vertical lines) were detected from a change-point analysis. (B) Change in variance across the range of normalized food abundance ranging from –1.5 to 2 standard deviations in eight classes. Variance below the threshold was 1.8 times higher than above it. (C and D) Similar relationships were present when data were pooled (C) for species within ecosystems and (D) for species pooled among ecosystems using the best-fitting asymptotic model (table S2). The Arctic Tern (not shown) model fit was not significant (table S1). The colors in (A) and (C) represent the data set for each ecosystem and in (D) for each seabird species.

The findings, just published in Science (Cury et al. 2011), show that seabirds are unable to increase their breeding output over a certain prey abundance. However, if the amount of prey falls below a threshold – which we estimated at one third of the observed maximum prey abundance – breeding success drops dramatically. This non-linear response has potentially important implications for management: If forage fish stocks are maintained above the identified threshold – seabird breeding success is likely sustainable. However, if fish stocks are harvested to below this level for extended periods of time, we are likely to observe decreasing breeding success and decreasing seabird populations. The study suggests that the one-third rule of thumb can be used as a precautionary guiding principle for marine management. So, potentially, we can use some basic principles from ecology to arrive at some basic principles for marine resource use.

The study highlights the importance of curiosity driven research and long term monitoring program. These monitoring programs were not primarily intended to inform management of marine resources but were instead set up by individuals with a keen interest in basic seabird ecology The study also underlines the importance of multidisciplinary collaboration for producing fun and exciting syntheses. Most of all, it highlights how rewarding it is to work with seabirds – coolest critters on the planet. Seabirds occupy some of the most remote and harsh habitats on the planet and are incredibly resilient – until critical thresholds are passed.